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  5. Asymptotic Analysis for Markovian models in non-equilibrium Statistical Mechanics
 
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Asymptotic Analysis for Markovian models in non-equilibrium Statistical Mechanics
File(s)
Ottobre-M-2012-PhD-Thesis.PDF (802.79 KB)
Author(s)
Ottobre, Michela
Type
Thesis or dissertation
Abstract
This thesis is mainly concerned with the problem of exponential convergence to equilibrium
for open classical systems. We consider a model of a small Hamiltonian system coupled to
a heat reservoir, which is described by the Generalized Langevin Equation (GLE) and we
focus on a class of Markovian approximations to the GLE. The generator of these Markovian
dynamics is an hypoelliptic non-selfadjoint operator. We look at the problem of exponential
convergence to equilibrium by using and comparing three different approaches: classic ergodic
theory, hypocoercivity theory and semiclassical analysis (singular space theory). In particular,
we describe a technique to easily determine the spectrum of quadratic hypoelliptic operators
(which are in general non-selfadjoint) and hence obtain the exact rate of convergence to
equilibrium.
Date Issued
2011
Date Awarded
2012-07
URI
http://hdl.handle.net/10044/1/9797
DOI
https://doi.org/10.25560/9797
Advisor
Pavliotis, Greg
Publisher Department
Mathematics
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)
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